Objective: This study aimed to evaluate the relationship between PREDICT tool overall survival (OS) scores and high-risk patients according to TAILORx risk categorization in elderly hormone reseptor (HR) positive human epidermal growth factor negative early breast-cancer patients.
Materials And Methods: We conducted a retrospective study, extracting data from medical records of 64 patients diagnosed with breast cancer. A retrospective analysis was performed on all patients who had Oncotype Dx Recurrence Scores across five medical centers between 2017 and 2022. PREDICT scores were defined as calculated 10-year OS rates via PREDICT tool.
Results: The median age of the patients was 67, with a range between 65-75 years. Low-risk patients had a slightly higher two PREDICT scores compared to high-risk patients (78% vs. 73%), (81% vs. 77%), which were statistically significant. The progesterone receptor (PR) level was significantly lower in the high-risk group (3.5% vs. 80%). A unit decrease in the PREDICT scores was associated with a 11% increase in the odds of being in the high-risk group. However, these effects weren't statistically significant in the multivariate analysis. A unit decrease in the PR level was significantly associated with increased odds (by 5% in the multivariate analysis) of being in the high-risk group.
Conclusion: Our study underscores the importance of using a combination of tools, including the PREDICT tool, PR levels, and TAILORx risk categorization, for a comprehensive risk assessment in these patients, especially in the older population. Accurate risk assessment is crucial for tailoring the treatment and optimizing outcomes in this vulnerable population. Future studies are warranted to further validate these findings in larger cohorts and to explore additional biomarkers and genomic signatures that may aid in the risk assessment and management of breast cancer in older patients.
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| http://dx.doi.org/10.4274/ejbh.galenos.2023.2023-8-5 | DOI Listing |
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